Most Recent Posts
Vitruvion: A Generative Model of Parametric CAD Sketches - 25 September 2021
2020
September 2020
Using 3D Printing to Develop Rapid-Response PPE Manufacturing - 28 September 2020
Video: Introduction to Convex Optimization - 27 September 2020
Video: Basics of Optimization - 20 September 2020
Video: Information Theory Basics - 13 September 2020
Video: The Gaussian Distribution - 6 September 2020
August 2020
Video: Useful Inequalities and Limit Theorems - 30 August 2020
Video: Dependence and Independence - 23 August 2020
Video: Basics of Joint Probability - 16 August 2020
Video: Some Useful Probability Distributions - 9 August 2020
Video: Probability Density and Mass Functions - 2 August 2020
July 2020
Video: Probability Spaces and Random Variables - 26 July 2020
Video: Why is Probability Important to Machine Learning? - 19 July 2020
Video: Why is the Gradient the Direction of Steepest Ascent - 12 July 2020
Video: Derivative as the Best Affine Approximation - 5 July 2020
June 2020
Video: Partial Derivatives - 28 June 2020
Video: Basics of Differentiation - 21 June 2020
The ELBO without Jensen, Kullback, or Leibler - 17 June 2020
Starting a YouTube Channel - 14 June 2020
2019
December 2019
Discrete Object Generation with Reversible Inductive Construction - 2 December 2019
July 2019
Lab Progress: Laser Cutter - 12 July 2019
June 2019
Efficient Optimization of Loops and Limits with Randomized Telescoping Sums - 14 June 2019
May 2019
Lab Progress: 3D Printer Enclosures - 1 May 2019
March 2019
Lab Complete: Assembling Tormach - 1 March 2019
2018
December 2018
A Bayesian Nonparametric View on Count-Min Sketch - 1 December 2018
August 2018
New Lab: Demolition - 24 August 2018
July 2018
Moved to Princeton! - 1 July 2018
2014
September 2014
Which research results will generalize? - 2 September 2014
2013
August 2013
Prior knowledge and overfitting - 26 August 2013
ICML Highlight: Fast Dropout Training - 1 August 2013
June 2013
Testing MCMC code, part 2: integration tests - 10 June 2013
Compressing genomes - 5 June 2013
May 2013
Testing MCMC code, part 1: unit tests - 20 May 2013
The Central Limit Theorem - 14 May 2013
JIT compilation in MATLAB - 13 May 2013
April 2013
Introspection in AI - 29 April 2013
Machine Learning Glossary - 22 April 2013
Optimal Spatial Prediction with Kriging - 21 April 2013
Fisher information - 8 April 2013
The Gumbel-Max Trick for Discrete Distributions - 6 April 2013
March 2013
Pseudo-marginal MCMC - 31 March 2013
Chernoff's bound - 25 March 2013
Upcoming Conferences - 24 March 2013
Variational Inference (part 1) - 22 March 2013
Geometric means of distributions - 18 March 2013
Learning Theory: What Next? - 15 March 2013
Stochastic memoization in Haskell - 14 March 2013
Data compression and unsupervised learning, Part 2 - 12 March 2013
An Auxiliary Variable Trick for MCMC - 11 March 2013
The Correct Birth/Death Jacobian for Mixture Models - 8 March 2013
A Geometric Intuition for Markov's Inequality - 7 March 2013
The Alias Method: Efficient Sampling with Many Discrete Outcomes - 3 March 2013
February 2013
What is representation learning? - 25 February 2013
High-Dimensional Probability Estimation with Deep Density Models - 22 February 2013
Data compression and unsupervised learning - 21 February 2013
A Parallel Gamma Sampling Implementation - 21 February 2013
Exponential Families and Maximum Entropy - 18 February 2013
Learning Theory: Purely Theoretical? - 15 February 2013
The Fundamental Matrix of a Finite Markov Chain - 15 February 2013
Disconnectivity graphs - 14 February 2013
Correlation and Mutual Information - 13 February 2013
Getting above the fray with lifted inference - 8 February 2013
Variograms, Covariance functions and Stationarity - 7 February 2013
What the hell is representation? * - 6 February 2013
Predictive learning vs. representation learning - 4 February 2013
January 2013
What is the Computational Capacity of the Brain? - 30 January 2013
Is AI scary? - 30 January 2013
Dealing with Reliability when Crowdsourcing - 29 January 2013
The Natural Gradient - 25 January 2013
Complexity of Inference in Bayesian Networks - 24 January 2013
It Depends on the Model - 24 January 2013
Markov chain centenary - 23 January 2013
Aversion of Inversion - 22 January 2013
Introductory post, and the invariance problem - 21 January 2013
DPMs and Consistency - 17 January 2013
Unbiased estimators of partition functions are basically lower bounds - 14 January 2013
Priors for Functional and Effective Connectivity - 11 January 2013
Computing Log-Sum-Exp - 9 January 2013
A Continuous Approach to Discrete MCMC - 7 January 2013
Bayesian nonparametrics in the real world - 4 January 2013
Asymptotic Equipartition of Markov Chains - 3 January 2013
Hashing, streaming and sketching - 2 January 2013
On representation and sparsity - 1 January 2013
2012
December 2012
Nonparanormal Activity - 27 December 2012
Discriminative (supervised) Learning - 26 December 2012
Method of moments - 25 December 2012
Should neurons be interpretable? - 24 December 2012
Turning Theory into Algorithms - 21 December 2012
The "Computation" in Computational Neuroscience - 20 December 2012
The Poisson Estimator - 19 December 2012
Learning Image Features from Video - 18 December 2012
Healthy Competition? - 17 December 2012
New Blog - 16 December 2012